Applied AI Engineer - Canada

Pulsora, Inc.•Calgary, AB

13d•CA$60,000 - CA$70,000•Hybrid

About The Position

We are seeking a highly skilled and experienced engineer who can independently build and scale full-stack products while designing and deploying reliable LLM-powered systems and agent workflows in production. Pulsora is the “Enterprise Sustainability Platform”, a well-funded Silicon Valley software startup dedicated to empowering purpose-driven enterprises to manage and improve their environmental, social, and governance (ESG) and overall sustainability footprint with an integrated, comprehensive, flexible, and innovative technology platform built for compliance, tracking, and insight.

Requirements

Bachelor’s degree in Computer Science, Engineering, or related field preferred (or equivalent hands on experience)
1-2 years of experience building AI-powered applications (AI agents or AI-assisted coding) and building and deploying LLM-powered applications or agents in production
Experience integrating major LLM APIs (e.g., OpenAI, Anthropic, Gemini, open-source)
Working knowledge of prompt design, context management (RAG, memory, tool use), and multi-step/agentic workflows
Ability to take products from concept to production and iteration across backend and frontend systems, including working across the full engineering lifecycle
Practical experience using tools like Claude Code, Cursor, OpenAI, Microsoft Copilot, including the ability to safely integrate AI-generated code into production (validation, CI/CD)
Experience debugging production issues, optimizing performance (latency, cost), and building maintainable systems
Ability to define evaluation strategies for AI outputs (quality, consistency, failure modes) and experience with AI-driven testing and reliability practices
Strong collaboration across a small team, including great communication with both onshore and offshore departments and translating vague requirements into actionable systems.
Self-motivated and proactive—you create momentum without needing direction
A strong problem solver who can navigate ambiguity
A builder who cares about shipping real, working products
Comfortable with ownership, accountability, and high expectations
Thrives outside of traditional work structures
You own the quality of the product you build

Nice To Haves

Build advanced agent systems (planning, orchestration, parallel execution)
Apply frameworks like LangChain, LangGraph, or similar where appropriate
Explore fine-tuning, evaluation frameworks, and benchmarking techniques
Contribute to intuitive, user-friendly AI-driven experiences and human-in-the-loop workflows
Ideally have industry and market knowledge of ESG and sustainability

Responsibilities

Build & Ship AI-Powered Products
Design, develop, and deploy LLM-powered applications and agent-based systems in production
Own the full product lifecycle from concept → production → iteration across backend and frontend
Build scalable, maintainable systems that solve real customer problems
Design & Operate GenAI Systems
Develop prompt strategies, context management (RAG, memory), and agent workflows
Integrate and optimize across leading LLM APIs (OpenAI, Anthropic, Gemini, open-source)
Continuously improve system quality, reliability, and performance
Leverage AI-First Development Workflows
Use AI-assisted coding tools (e.g., Cursor, Copilot, Claude Code) to accelerate development
Validate, test, and safely integrate AI-generated code into production systems
Contribute to evolving best practices for AI-first engineering
Ensure Quality, Reliability & Performance
Own testing strategy including unit, integration, and end-to-end testing
Define and implement evaluation frameworks for AI outputs (quality, consistency, failure modes)
Debug production issues and optimize for latency, cost, and scalability
Take full ownership of system reliability and production stability
Collaborate & Execute in Fast-Moving Environments
Translate ambiguous requirements into working solutions
Partner with product, design, and customer-facing teams to deliver impactful features
Collaborate effectively with distributed and offshore engineering teams
Advance AI & Product Capabilities (Nice to Have Contributions)
Build advanced agent systems (planning, orchestration, parallel execution)
Apply frameworks like LangChain, LangGraph, or similar where appropriate
Explore fine-tuning, evaluation frameworks, and benchmarking techniques
Contribute to intuitive, user-friendly AI-driven experiences and human-in-the-loop workflows